ICAR AICE-JRF/SRF Advanced Dairy Engineering: practice questions

1 · Transport phenomena in dairy processes · medium

The Chilton–Colburn analogy states that:

1. Nu = 0.023 Re^0.8 Pr^0.4 for every geometry and flow regime
2. Sh = 2 for all spheres (stagnant fluid limit)
3. f = 64/Re in turbulent flow
4. j_H = St Pr^(2/3) = f/2

2 · Spray dryer modelling and computational fluid dynamics · hard

A soft sensor for milk powder moisture in a dryer is usually based on:

1. Visual inspection of the powder colour by operators each hour
2. Feed fat content alone
3. Ambient noise
4. Calibrated heat and mass balances

3 · Spray dryer modelling and computational fluid dynamics · hard

A key limitation of current spray dryer CFD is:

1. Agglomeration and collisions
2. An inability to model air flow at all inside large chambers
3. Ignoring gravity
4. Requiring no validation

4 · Freezing and thawing models · hard

Microwave tempering of frozen dairy blocks risks runaway heating because:

1. Ice absorbs microwaves more strongly than water
2. Liquid water absorbs microwaves more than ice
3. Fat freezes faster than water
4. Microwaves cool the surface

5 · Process simulation software · medium

A major difficulty when simulating dairy plants in general chemical simulators is:

1. A complete lack of unit operations such as heat exchangers and pumps
2. Inability to calculate mass balances
3. Missing dairy property data
4. No support for water as a component

6 · Process simulation software · medium

A digital twin is a model that is:

1. Continuously updated with plant data
2. A copy of the plant built in another country
3. A static design drawing
4. A spreadsheet of costs only

7 · Process simulation software · medium

Data reconciliation in a digital twin:

1. Deletes all measurements that disagree with the design values
2. Adds fictitious streams to hide errors
3. Ignores sensor uncertainty completely
4. Adjusts data to close balances

8 · Pressure vessel and heat exchanger design codes · medium

Thin-walled evaporator bodies under vacuum must be designed mainly against:

1. Internal bursting at high pressure
2. Creep at 500 °C
3. Hydrogen embrittlement
4. Buckling

9 · Advanced control and machine learning in dairy plants · hard

Why must pasteurisation flow diversion not depend on a machine-learning model?

1. Safety functions need simple, validated logic
2. Machine learning cannot read temperature signals from sensors
3. Regulators ban computers in dairies
4. Models are too slow for any purpose

10 · Sustainability engineering: energy and water pinch analysis · medium

In dairy product life-cycle assessments, the largest share of emissions usually comes from:

1. Processing electricity
2. On-farm emissions
3. Packaging
4. Retail lighting